Prosecution Insights
Last updated: August 16, 2026
Application No. 18/561,388

DEVICE FOR ESTIMATING ACTIVE CLAY CONTENT, DEVICE FOR GENERATING LEARNED MODEL, METHOD FOR ESTIMATING ACTIVE CLAY CONTENT, AND METHOD FOR GENERATING LEARNED MODEL

Non-Final OA §101§102§103
Filed
Nov 16, 2023
Priority
Sep 28, 2021 — JP 2021-158416 +1 more
Examiner
NGUYEN, LAM S
Art Unit
2853
Tech Center
2800 — Semiconductors & Electrical Systems
Assignee
Sintokogio Ltd.
OA Round
1 (Non-Final)
79%
Grant Probability
Favorable
1-2
OA Rounds
0m
Est. Remaining
80%
With Interview

Examiner Intelligence

Grants 79% — above average
79%
Career Allowance Rate
1116 granted / 1416 resolved
+10.8% vs TC avg
Minimal +1% lift
Without
With
+0.9%
Interview Lift
resolved cases with interview
Typical timeline
2y 8m
Avg Prosecution
58 currently pending
Career history
1473
Total Applications
across all art units

Statute-Specific Performance

§101
3.1%
-36.9% vs TC avg
§103
46.2%
+6.2% vs TC avg
§102
34.0%
-6.0% vs TC avg
§112
7.8%
-32.2% vs TC avg
Black line = Tech Center average estimate • Based on career data from 1416 resolved cases

Office Action

§101 §102 §103
DETAILED ACTION Notice of Pre-AIA or AIA Status The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . Claim Rejections - 35 USC § 101 35 U.S.C. 101 reads as follows: Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title. Claims 5 and 8 are rejected under 35 U.S.C. 101 because: The claims recite the act of outputting an active clay content from the information concerning mixed sand. This is a well-known act in the art as addressed in the rejection below. The claims even though cite that such act is performed by a machine learning mode, the claim language does not specify more about the machine learning model, it is therefore considered as generic. As a result, the use of the one or more machine learning models as claimed is directed to the abstract idea of using a generic machine learning model/technique in a particular/new environment or to a particular field of use, with no invention concept (Recentive Analytics, Inc v. Fox Corp (Fed Cir, 2023-2437, 4/18/2025)). Claim Rejections - 35 USC § 102 The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action: A person shall be entitled to a patent unless – (a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention. Claim(s) 1-4, 7, and 9 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Ozaki (JP 2004042111). Regarding to claims 1, 9: Ozaki discloses an active clay content estimation device comprising: one or more processors, the one or more processors being configured to execute: an obtaining step of obtaining information concerning mixed sand with which green sand containing clay is mixed (FIG. 2: The information of the green sand 14, regarding to the tensile breaking load, is measured by the load cell 20); and an estimating step of estimating an active clay content in the mixed sand in accordance with the information concerning the mixed sand (paragraph [0032]: The mixing ratio of the active clay is determined from the tensile breaking load, and the amount of active clay supplied is adjusted). Regarding to claim 2: wherein the information concerning the mixed sand includes either or both of a compressive strength and a shear strength of the mixed sand (paragraph [0032]: The tensile breaking load is measured due to the compression on the green sand in the recess). Regarding to claim 3: wherein the information concerning the mixed sand further includes at least one parameter selected from the group consisting of a moisture content, a permeability, compactability, and a sand temperature of the mixed sand (paragraph [0032]: The tensile breaking load measured due to the compression on the green sand in the recess reads on the compactability). Regarding to claims 4, 7: wherein the information concerning the mixed sand includes at least one at least one parameter selected from the group consisting of an added amount of silica sand, an added amount of the clay, and an added amount of an additive that is not the clay (paragraphs [0032]-[0033]: The amount of active clay is adjusted and added to the predetermined mixing ratio). Claim Rejections - 35 USC § 103 The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action: A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made. Claim(s) 5 and 8 is/are rejected under 35 U.S.C. 103 as being unpatentable over Ozaki (JP 2004042111) in view of Deepak (WO 2014132269). Ozaki discloses the claimed invention as discussed above, except wherein in the estimating step, the one or more processors estimate the active clay content in the mixed sand with use of a trained model that is constructed by machine learning and that takes, as an input, the information concerning the mixed sand and outputs the active clay content. Deepak discloses a computer implemented system for optimization of sand of reducing casting rejections 3 Docket No. 12480-000843-US-NP 6. (Currently amended) The active clay content estimation device as set forth in-any one of claims 1 to 4 claim 1, wherein the one or more processors are configured to further execute: an output step of outputting an alert in a case where the active clay content estimated in the estimating step satisfies a given condition. 7. (Currently amended) The active clay content estimation device as set forth in-any one of claims 1 to 4 claim 1, wherein the one or more processors are configured to further execute: a determining step of determining an added amount of the clay in accordance with the active clay content estimated in the estimating step. 8. (Original) A trained model generation device comprising: one or more processors, the one or more processors being configured to execute: a constructing step of constructing, by machine learning, a trained model that takes, as an input, information concerning mixed sand with which green sand containing clay is mixed and outputs an active clay content in the mixed sand. 9. (Original) An active clay content estimation method comprising the steps executed by one or more processors, the steps being: an obtaining step of obtaining information concerning mixed sand with which green sand containing clay is mixed; and an estimating step of estimating an active clay content in the mixed sand in accordance with the information concerning the mixed sand. 10. (Cancelled) END OF CLAIM LISTING 4
Read full office action

Prosecution Timeline

Nov 16, 2023
Application Filed
Jul 22, 2026
Non-Final Rejection mailed — §101, §102, §103 (current)

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Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

1-2
Expected OA Rounds
79%
Grant Probability
80%
With Interview (+0.9%)
2y 8m (~0m remaining)
Median Time to Grant
Low
PTA Risk
Based on 1416 resolved cases by this examiner. Grant probability derived from career allowance rate.

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